Open Source Python Image Processing Software for Mac

This is the main repository for the SciPy library, one of the core packages that make up the SciPy stack. SciPy is an open source software used in the fields of mathematics, science, and engineering, with modules for statistics, optimization, integration, linear algebra, signal and image processing, and many more. The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. Both SciPy and NumPy run on all popular operating systems, are fast and easy to install, and are powerful yet easy to use. They’re currently depended upon by numerous leading scientists and engineers all over the world. Try them for yourself!

NOTE: the project has moved to https://scipy.org/scipylib/ --- go there to find latest versions. This sourceforge project contains only old historical versions of the software. SciPy is package of tools for science and engineering for Python. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.

LaueTools is an open-source project for white beam Laue x-ray microdiffraction data analysis including tools in image processing, peaks searching & indexing, crystal structure solving (orientation & strain) and data & grain mapping visualisation. Python 3 Code and new features are now at: https://gitlab.esrf.fr/micha/lauetools

The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with graphical user interfaces and/or via the command-line. See our YouTube channel for tutorial videos via the homepage. The applications are all built out of a uniform user-interface framework that provides a very high level (Qt) interface to powerful image processing and scientific visualisation algorithms from the Insight Toolkit (ITK) and Visualisation Toolkit (VTK). The framework allows one to build stand-alone medical imaging applications quickly and easily.

ImageJ is a public domain Java image processing program inspired by NIH Image for the Macintosh. It runs, either as an online applet or as a downloadable application, on any computer with a Java 1.1 or later. HOME @ http://rsb.info.nih.gov/ij/

Image Processing software for combining information from images of the same scene, but with illumination variations or small changes. This work is the result of the coursework of an Image Processing regular course at IMPA.

MIPPY is a minimalistic DICOM image browser with built-in image processing modules. Its modular design means it can be extended with any number of user-created modules for image processing and analysis.

Written in Python and the Numeric package. It supports the examples of the book: Dougherty and Lotufo, Hands-on Morphological Image Proc., SPIE, 2003, ISSN=0-8194-4720-X. This toolbox has been continued at www.adessowiki.org under name ia870.

The OpenCMISS-Zinc Library (opencmiss.org/zinc), or Zinc, is a software library for building interactive graphical modelling and visualisation applications. Models are represented in Zinc as mathematical fields defined over domains, including finite elements with support for high-order basis functions, complex parameter mappings and time variation, and image-based fields. Further fields can be defined by mathematical expressions and algorithms on existing fields, including image processing filters. Zinc model data structures are dynamic, supporting interactive applications which programmatically create, destroy and modify parts of models.

Pink is an image processing library developed at ESIEE Engineering for research and teaching purposes. It contains implementations of over 200 algorithms for image segmentation and filtering.

Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.

Composight is a cross-platform toolkit for 3D-image processing in the domain of composite materials science. It is written in C++ and provides small, problem-specific applications for viewing, filtering and segmentation of volumetric data such as micro-CT scans. The main objective is not to provide yet another complex application for volume data visualization and medical image processing. Instead, Composight is a collection of small and simple apps that have already been successfully used to solve various problems in materials science.

GeoSciPy is a set of C and Python functions that provide an API for all aspects of Geoscience and Remote Sensing Applications. Functions include reading/writing of many data formats, images, vectors, ..., and processing of images, vectors, ... including map projections, ... The library is written C, using HDF5 as the file format for storage of all remotely-sensed data and ancillary data, as well as processed data. The C functions assume a particular format for the HDF5 file contents, and provide functions for reading and writing data to such files. There is also a Python API that provides a procedural as well as an object-oriented interface to these functions. A Python GUI for interacting with such datasets is also part of the project. While there are other open-source GIS, and image-processing packages available, this one is designed to be comprehensive, work on 3 major platforms, user-extensible, fast, and able to handle huge datasets. Click the Blog tab for more info.

XMIPP is an image processing suite for 3D-reconstruction of biological specimens from transmission electron microscopy data. NOTE that stable releases (including binaries) are longer stored at Sourceforge, but are available at http://xmipp.cnb.csic.es